Azure Document Translation client library for JavaScript - version 1.0.0

Document Translation is a cloud-based machine translation feature of the Azure AI Translator service. You can translate multiple and complex documents across all supported languages and dialects while preserving original document structure and data format. The Document Translation API supports two translation processes:

Asynchronous batch translation supports the processing of multiple documents and large files. The batch translation process requires an Azure Blob storage account with storage containers for your source and translated documents.

Synchronous single file translation supports the processing of single file translations. The file translation process doesn't require an Azure Blob storage account. The final response contains the translated document and is returned directly to the calling client.

The following operations are supported by the Document Translation feature:

  • Synchronous document translation: Used to synchronously translate a single document. The method doesn't require an Azure Blob storage account.
  • Start batch translation: Used to execute an asynchronous batch translation request. The method requires an Azure Blob storage account with storage containers for your source and translated documents.
  • Get status for all translation jobs: Used to request a list and the status of all translation jobs submitted by the user (associated with the resource).
  • Get status for a specific translation job: Used to request the status of a specific translation job. The response includes the overall job status and the status for documents that are being translated as part of that job.
  • Get status for all documents: Used to request the status for all documents in a translation job.
  • Get status for a specific document: Returns the status for a specific document in a job as indicated in the request by the id and documentId query parameters.
  • Cancel translation: Cancels a translation job that is currently processing or queued (pending). An operation isn't canceled if already completed, failed, or still canceling.
  • Get supported formats: Returns a list of document or glossary formats supported by the Document Translation feature.

Key links:

Getting started

Currently supported environments

See our support policy for more details.

Prerequisites

Install the @azure/ai-translation-document package

Install the Azure Document Translation client library for JavaScript with npm:

npm install @azure/ai-translation-document

Set up Azure Blob Storage account

Batch translation requires an Azure Blob Storage account. For more information about creating an Azure Blob Storage account see here. For creating containers for your source and target files see here. Make sure to authorize your Translation resource storage access, more info here.

When "Allow Storage Account Key Access" is disabled on the storage account, Managed Identity is enabled on the Translator resource, and it is assigned the role "Storage Blob Data Contributor" on the storage account, then you can use the container URLs directly and no SAS URIs will need to be generated.

Authenticate the client

This library exposes two clients:

  • DocumentTranslationClient for batch translation and translation status operations.
  • SingleDocumentTranslationClient for synchronous single-document translation.

Both clients can authenticate with a Microsoft Entra credential or an API key.

Using a Microsoft Entra credential

You can authenticate with Microsoft Entra ID using a credential from the @azure/identity library. To use the DefaultAzureCredential provider shown below, or other credential providers provided with the Azure SDK, please install the @azure/identity package:

npm install @azure/identity

You will also need to register a new Microsoft Entra application and grant access to the Translator resource by assigning a suitable role to your service principal.

Using Node.js and Node-like environments, you can use the DefaultAzureCredential class to authenticate the client:

import { DocumentTranslationClient } from "@azure/ai-translation-document";
import { DefaultAzureCredential } from "@azure/identity";

const endpoint = "https://<translator-instance>.cognitiveservices.azure.com";
const client = new DocumentTranslationClient(endpoint, new DefaultAzureCredential());

For browser environments, use the InteractiveBrowserCredential from the @azure/identity package to authenticate:

import { InteractiveBrowserCredential } from "@azure/identity";
import { DocumentTranslationClient } from "@azure/ai-translation-document";

const credential = new InteractiveBrowserCredential({
  tenantId: "<YOUR_TENANT_ID>",
  clientId: "<YOUR_CLIENT_ID>",
});
const client = new DocumentTranslationClient("<endpoint>", credential);

Using an API key

You can also authenticate with the resource's API key using a KeyCredential:

import { KeyCredential } from "@azure/core-auth";
import { DocumentTranslationClient } from "@azure/ai-translation-document";

const endpoint = "https://<translator-instance>.cognitiveservices.azure.com";
const credential: KeyCredential = { key: "YOUR_SUBSCRIPTION_KEY" };
const client = new DocumentTranslationClient(endpoint, credential);

JavaScript Bundle

To use this client library in the browser, first you need to use a bundler. For details on how to do this, please refer to our bundling documentation.

Key concepts

DocumentTranslationClient

DocumentTranslationClient is the interface for asynchronous batch translation and for querying translation and document status. Batch translation requires an Azure Blob Storage account with containers for your source and translated documents.

SingleDocumentTranslationClient

SingleDocumentTranslationClient is the interface for synchronous single-document translation. It doesn't require an Azure Blob Storage account; the translated document is returned directly in the response.

Examples

The following section provides several code snippets covering the main features of this client library.

Synchronous document translation

Used to synchronously translate a single document. The method doesn't require an Azure Blob storage account.

import { SingleDocumentTranslationClient } from "@azure/ai-translation-document";
import { DefaultAzureCredential } from "@azure/identity";
import { writeFile } from "node:fs/promises";

const endpoint = "https://<translator-instance>.cognitiveservices.azure.com";
const client = new SingleDocumentTranslationClient(endpoint, new DefaultAzureCredential());
const response = await client.translate("hi", {
  document: {
    contents: "This is a test.",
    contentType: "text/html",
    filename: "test-input.txt",
  },
});
if (response.readableStreamBody) {
  await writeFile("test-output.txt", response.readableStreamBody);
}

Batch document translation

Used to execute an asynchronous batch translation request. The method requires an Azure Blob storage account with storage containers for your source and translated documents. Provide the source and target container URLs (with SAS tokens if required) and poll until the operation completes.

import { DocumentTranslationClient } from "@azure/ai-translation-document";
import { DefaultAzureCredential } from "@azure/identity";

const endpoint = "https://<translator-instance>.cognitiveservices.azure.com";
const client = new DocumentTranslationClient(endpoint, new DefaultAzureCredential());
const poller = client.startTranslation({
  inputs: [
    {
      source: { sourceUrl: "<source container SAS URL>" },
      targets: [{ targetUrl: "<target container SAS URL>", language: "fr" }],
    },
  ],
});
const result = await poller.pollUntilDone();
console.log(`Translation status: ${result.status}`);

Get supported formats

Returns a list of document formats supported by the Document Translation feature.

import { DocumentTranslationClient } from "@azure/ai-translation-document";
import { DefaultAzureCredential } from "@azure/identity";

const endpoint = "https://<translator-instance>.cognitiveservices.azure.com";
const client = new DocumentTranslationClient(endpoint, new DefaultAzureCredential());
const formats = await client.getSupportedFormats("Document");
for (const format of formats.value) {
  console.log(format.format);
}

Troubleshooting

Logging

Enabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the AZURE_LOG_LEVEL environment variable to info. Alternatively, logging can be enabled at runtime by calling setLogLevel in the @azure/logger:

import { setLogLevel } from "@azure/logger";

setLogLevel("info");

For more detailed instructions on how to enable logs, you can look at the @azure/logger package docs.

Contributing

If you'd like to contribute to this library, please read the contributing guide to learn more about how to build and test the code.

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